stochasticarchitecture
StochasticArchitectures
We take 1000 training images from CIFAR-10 as a fixed batch, randomly sample the neural architecture for inference, and computevar(µ) of the last BN layer of a NSA and a NSA-i trained givenS = 5000architectures. Inthissection, wecalculate thetestaccuracyof200randomly sampled architectures based onthe vanilla NSA models trained under various spaces. A half of these architectures are seen during trainingwhiletheotherhalfnot.
Country:
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.07)
- Asia > China > Beijing > Beijing (0.07)
UnderstandingandExploringtheNetworkwith StochasticArchitectures
The predictions provided by different architectures can be further assembled or used to calculate uncertainty estimates, making the prediction model more accurate,robust,andcalibrated.
Country:
- Asia > China > Beijing > Beijing (0.04)
- North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.95)